Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness

Passive acoustic monitoring (PAM) using autonomous recording units (ARUs) has become a key tool in long-term, low-cost ecological studies. However, one of the main challenges lies in storing and analyzing the large volume of data it generates, which requires significant processing effort and species annotation. In this context, it is crucial to establish a sampling and acoustic data analysis protocol that maximizes the efficiency of ecological information retrieval. This study proposes the application of the species-area relationship (SAR) mathematical model to optimize the use of ARUs and reduce the effort required for acoustic data analysis, aiming to predict the number of detected species in three Neotropical ecoregions: Amazonia, Caatinga, and Campos y Malezales. Our results suggest that increasing the number of ARUs (12 in this study) while reducing the post-recording listening effort (12 minutes per ARU) enhances sampling efficiency, allowing for a more accurate representation of ..., , # Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness

Dataset DOI: [10.5061/dryad.0rxwdbsdd](10.5061/dryad.0rxwdbsdd)

## Description of the data and file structure

This dataset compiles avian occurrence records obtained through passive acoustic monitoring within the Campos and Malezales ecoregion of Argentina. The analysis is based on 1,152 one-minute audio recordings collected using autonomous recording units (ARUs). Each audio file was manually inspected to identify all vocally detected species. These data form part of a standardized series of acoustic matrices for Neotropical biomes, ensuring compatibility and comparability across studies. Their principal value lies in providing organized and reusable information on avian richness and occurrence at a per-minute recording scale. This granularity facilitates subsequent analyses on diversity, acoustic patterns, and the optimization of pass...,